Abstract: A region-based illumination-normalization method and system utilizes a plurality of filters to filter a test image for obtaining a high frequency image and a low pass image. The low pass image is segmented into several regions by an image segmentation unit so that a region-based adjustment unit normalizes the regions based on an illumination reference model, respectively. Finally, an image combination unit is employed to combine the high frequency image and the low pass image that is normalized.

Abstract: The present invention relates to methods and systems for an illuminant compensation. In particular, these methods and systems include a method for operations on an image, for example, an image of a human face. In the described methods and systems, it is determined for each pixel in the image whether it is part of the face region. A surface fitting is then determined based on only the pixels that are determined to be part of the face region. Also, described are methods and systems for image normalization wherein the standard deviation and average for the gray levels of the pixels are determined and then used to normalize the image so that the gray level for each of the pixels falls between a particular range.

Abstract: The present invention discloses an image preprocessing method capable of increasing the accuracy of face detection by enhancing the contrast between dark pixels and their surrounding bright pixels, and increasing the brightness difference between dark pixels and bright pixels. Even in insufficient and non-uniform lighting conditions, the eye-analogue segments of a human face are obvious; so as to make a subsequent algorithm using eye-analogue segments for detecting human faces and producing more accurate results.

Abstract: A region-based illumination-normalization method and system utilizes a plurality of filters to filter a test image for obtaining a high frequency image and a low pass image. The low pass image is segmented into several regions by an image segmentation unit so that a region-based adjustment unit normalizes the regions based on an illumination reference model, respectively. Finally, an image combination unit is employed to combine the high frequency image and the low pass image that is normalized.

Abstract: The present invention discloses an image preprocessing method capable of increasing the accuracy of face detection by enhancing the contrast between dark pixels and their surrounding bright pixels, and increasing the brightness difference between dark pixels and bright pixels. Even in insufficient and non-uniform lighting conditions, the eye-analogue segments of a human face are obvious; so as to make a subsequent algorithm using eye-analogue segments for detecting human faces and producing more accurate results.

Abstract: The present invention relates to methods and systems for an illuminant compensation. In particular, these methods and systems include a method for operations on an image, for example, an image of a human face. In the described methods and systems, it is determined for each pixel in the image whether it is part of the face region. A surface fitting is then determined based on only the pixels that are determined to be part of the face region. Also, described are methods and systems for image normalization wherein the standard deviation and average for the gray levels of the pixels are determined and then used to normalize the image so that the gray level for each of the pixels falls between a particular range.